Image segmentation with a finite element method
The Mumford-Shah functional for image segmentation is an original approach of the image segmentation problem, based on a minimal energy criterion. Its minimization can be seen as a free discontinuity problem and is based on Γ-convergence and bounded variation functions theories. Some new regularization results, make possible to imagine a finite element resolution method. In a first time, the Mumford-Shah functional is introduced and some existing results are quoted. Then, a discrete formulation...
Given a separable metric locally compact space , and a positive finite non-atomic measure on , we study the integral representation on the space of measures with bounded variation of the lower semicontinuous envelope of the functional with respect to the weak convergence of measures.
We study the integral representation properties of limits of sequences of integral functionals like under nonstandard growth conditions of -type: namely, we assume thatUnder weak assumptions on the continuous function , we prove -convergence to integral functionals of the same type. We also analyse the case of integrands depending explicitly on ; finally we weaken the assumption allowing to be discontinuous on nice sets.
We study the integral representation properties of limits of sequences of integral functionals like under nonstandard growth conditions of (p,q)-type: namely, we assume that Under weak assumptions on the continuous function p(x), we prove Γ-convergence to integral functionals of the same type. We also analyse the case of integrands f(x,u,Du) depending explicitly on u; finally we weaken the assumption allowing p(x) to be discontinuous on nice sets.
Diamo condizioni sulle funzioni , e sulla misura affinché il funzionale sia -semicontinuo inferiormente su . Affrontiamo successivamente il problema del rilassamento.